问题描述
我正在尝试动手执行numpy,在遇到以下数据类型时会碰到使用内置方法dtype.以下是我得到的一些结果.你能解释一下u11意味着什么吗?
I am trying to do hands on the numpy, i cam across following datatype whenused inbuilt method dtype.Following the few results i have got.Can you please explain what it means by u11
a1 = np.array([3,5,'p'])
print(a1.dtype)
o/p => U11
o/p = >U11
推荐答案
PyArrayObject
类型具有 NPY_PRIORITY
属性,该属性表示应视为数组dtype
的类型的优先级如果它包含具有不同数据类型的项目.您可以使用 PyArray_GetPriority
API,该API返回 __array_priority__
属性(转换为双精度),则该名称或属性不存在.在这种情况下,Unicode比整数类型具有更高的优先级,这就是a1.dtype
返回U11
的原因.
Numpy's array objects that are PyArrayObject
types have a NPY_PRIORITY
attribute that denotes the priority of the type in which should be considered as the array's dtype
in cases that it contains items with heterogeneous data types. You can access to this priority using PyArray_GetPriority
API which Returns the __array_priority__
attribute (converted to a double) of obj or def if no attribute of that name exists. In this case Unicode has a more priority than integer type and that's why a1.dtype
returns U11
.
现在,关于U11
或通常的U#
,它由两部分组成. U
表示Unicode dtype
,而#
表示它可以容纳的元素数.不过,在不同的平台上,这可能会有所不同.
Now, regarding the U11
or in general U#
, it consists of two parts. The U
which denotes a Unicode dtype
and the #
denotes the number of elements it can hold. This may be different in different platforms though.
In [45]: a1.dtype
Out[45]: dtype('<U21') # 64bit Linux
In [46]: a1.dtype.type # The type object used to instantiate a scalar of this data-type.
Out[46]: numpy.str_
In [49]: a1.dtype.itemsize
Out[49]: 84 # 21 * 4
在文档 https://docs.scipy.org/doc/numpy-1.14.0/reference/arrays.dtypes.html#data-type-objects-dtype .
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